Phenomenal growth in computational power from 1970 through 2010 enabled a parallel expansion in linear model methodology. From humble beginnings in agriculture, linear model applications are now essential in sciences of genetics, education, and biostatistics, to name a few. Indeed, the meaning of "linear models " has evolved accordingly. Developers at SAS Institute have been in the forefront of invention and implementation of these methods at the core of statistical science. Pathways will be traced in steps of SAS ® procedures, beginning with GLM and REG, proceeding through VARCOMP, NLIN, MIXED and GENMOD, and arriving at NLMIXED and GLIMMIX. Along the way, some problems have disappeared, new ones have emerged, and others are still along for the ride
To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.